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Last update: 08/10/2025

langchain-classic

🦜🔗 Build context-aware reasoning applications

Latest version: 1.0.0a1 registry icon
Maintenance score
100
Safety score
100
Popularity score
100
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Security
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1.0.0a1 0 0 0 0 0

Stability
Latest release:

1.0.0a1 - This version is safe to use because it has no known security vulnerabilities at this time. Find out if your coding project uses this component and get notified of any reported security vulnerabilities with Meterian-X Open Source Security Platform

Licensing

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MIT   -   MIT License

Not a wildcard

Not proprietary

OSI Compliant

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The platform for reliable agents.

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LangChain is a framework for building LLM-powered applications. It helps you chain together interoperable components and third-party integrations to simplify AI application development — all while future-proofing decisions as the underlying technology evolves.

pip install -U langchain

Documentation: To learn more about LangChain, check out the docs.

If you're looking for more advanced customization or agent orchestration, check out LangGraph, our framework for building controllable agent workflows.

[!NOTE] Looking for the JS/TS library? Check out LangChain.js.

Why use LangChain?

LangChain helps developers build applications powered by LLMs through a standard interface for models, embeddings, vector stores, and more.

Use LangChain for:

  • Real-time data augmentation. Easily connect LLMs to diverse data sources and external/internal systems, drawing from LangChain’s vast library of integrations with model providers, tools, vector stores, retrievers, and more.
  • Model interoperability. Swap models in and out as your engineering team experiments to find the best choice for your application’s needs. As the industry frontier evolves, adapt quickly — LangChain’s abstractions keep you moving without losing momentum.

LangChain’s ecosystem

While the LangChain framework can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools when building LLM applications.

To improve your LLM application development, pair LangChain with:

  • LangSmith - Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
  • LangGraph - Build agents that can reliably handle complex tasks with LangGraph, our low-level agent orchestration framework. LangGraph offers customizable architecture, long-term memory, and human-in-the-loop workflows — and is trusted in production by companies like LinkedIn, Uber, Klarna, and GitLab.
  • LangGraph Platform - Deploy and scale agents effortlessly with a purpose-built deployment platform for long-running, stateful workflows. Discover, reuse, configure, and share agents across teams — and iterate quickly with visual prototyping in LangGraph Studio.

Additional resources

  • Conceptual Guides: Explanations of key concepts behind the LangChain framework.
  • Tutorials: Simple walkthroughs with guided examples on getting started with LangChain.
  • API Reference: Detailed reference on navigating base packages and integrations for LangChain.
  • LangChain Forum: Connect with the community and share all of your technical questions, ideas, and feedback.
  • Chat LangChain: Ask questions & chat with our documentation.